README.md

metadata

license: agpl-3.0
library_name: pytorch
tags:
  - static2dynamic
  - diffusion
  - generative-modeling
  - biology
  - microscopy
  - image-to-video
  - trajectory-inference
pipeline_tag: image-to-video

Static2Dynamic

Pretrained checkpoints for Static2Dynamic, a method for reconstructing videos of unobservable cellular, developmental, and disease processes from static, unpaired snapshots.

• Code repository
• Preprint

Checkpoints

Each checkpoint subfolder contains:

• net/: diffusion model config and weights
• video_time_encoder/: time conditioning encoder config and weights
• dynamic/: scheduler configuration
• my_conf/: run configuration
• train_samples.parquet: training split samples
• test_samples.parquet: test split samples
• pseudotime_predictions/: pseudotime predictions

Download example

Download one checkpoint folder:

hf download thethomasboyer/Static2Dynamic --include 'NASH_steato/*' --local-dir ./Static2Dynamic_models